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Claude’s memory architecture is the opposite of ChatGPT’s

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Re: Claude’s memory architecture is the opposite of ChatGPT’s

#31
post #13

They are changing the way memory works soon, too: https://x.com/btibor91/status/1965906564692541621 Edit: They apparently just announced this as well: https://www.anthropic.com/news/memory

Would be very sad if they remove the current memory system for this.

Re: Claude’s memory architecture is the opposite of ChatGPT’s

#32

Earlier quoted context omitted.

What is "actual intelligence" and how are you different from a Markov chain?

What I mean is that the current generation of LLMs don’t understand how concepts relate to one another. Which is why they’re so bad at maths for instance. Markov chains can’t deduce anything logically. I can.

[deleted]

Re: Claude’s memory architecture is the opposite of ChatGPT’s

#33
post #30

Earlier quoted context omitted.

> It may actually be the final breakthrough we need for AGI. I disagree. As I understand them, LLMs right now don’t understand concepts. They actually don’t understand, period. They’re basically Markov chains on steroids. There is no intelligence in this, and in my opinion actual intelligence is a prerequisite for AGI.

How do you define "LLMs don't understand concepts"? How do you define "understanding a concept" - what do you get if a system can "understand" concept vs not "understanding" a concept?

That's a good question. I think I might classify that as solving a novel problem. I have no idea if LLMs can do that consistently currently. Maybe they can.

The idea that "understanding" may be able to be modeled with general purpose transformers and the connections between words doesn't sound absolutely insane to me.

But I have no clue. I'm a passenger on this ride.

Re: Claude’s memory architecture is the opposite of ChatGPT’s

#34
post #9

The link to the breakdown of ChatGPT's memory implementation is broken, the correct link is: https://www.shloked.com/writing/chatgpt-memory-bitter-lesson This is really cool, I was wondering how memory had been implemented in ChatGPT. Very interesting to see the completely different approaches. It seems to me like Claude's is better suited for solving technical tasks while ChatGPT's is more suited to improving casual…

> It may actually be the final breakthrough we need for AGI. I disagree. As I understand them, LLMs right now don’t understand concepts. They actually don’t understand, period. They’re basically Markov chains on steroids. There is no intelligence in this, and in my opinion actual intelligence is a prerequisite for AGI.

They are capable of extracting arbitrary semantic information and generalize across it. If this is not an understanding, I don't know what is.

Re: Claude’s memory architecture is the opposite of ChatGPT’s

#35
post #9

The link to the breakdown of ChatGPT's memory implementation is broken, the correct link is: https://www.shloked.com/writing/chatgpt-memory-bitter-lesson This is really cool, I was wondering how memory had been implemented in ChatGPT. Very interesting to see the completely different approaches. It seems to me like Claude's is better suited for solving technical tasks while ChatGPT's is more suited to improving casual…

You don't want an AGI. How do you make it obey?

Re: Claude’s memory architecture is the opposite of ChatGPT’s

#36
post #4

I love Claude's memory implementation, but I turned memory off in ChatGPT. I use ChatGPT for too many disparate things and it was weird when it was making associations across things that aren't actually associated in my life.

It's funny, I can't get ChatGPT to remember basic things at all. I'm using it to learn a language (I tried many AI tutors and just raw ChatGPT was the best by far) and I constantly have to tell it to speak slowly. I will tell it to remember this as a rule and to do this for all our conversations but it literally can't remember that. It's strange. There are other things too.

Re: Claude’s memory architecture is the opposite of ChatGPT’s

#37
The difference is implementation comes down to business goals more than anything.

There is a clear directionality for ChatGPT. At some point they will monetize by ads and affiliate links. Their memory implementation is aimed at creating a user profile.

Claude's memory implementation feels more oriented towards the long term goal of accessing abstractions and past interactions. It's very close to how humans access memories, albeit with a search feature. (they have not implemented it yet afaik), there is a clear path where they leverage their current implementation w RL posttraining such that claude "remembers" the mistakes you pointed out last time. It can in future iterations derive abstractions from a given conversation (eg: "user asked me to make xyz changes on this task last time, maybe the agent can proactively do it or this was the process last time the agent did it").

At the most basic level, ChatGPT wants to remember you as a person, while Claude cares about how your previous interactions were.

Re: Claude’s memory architecture is the opposite of ChatGPT’s

#38

Earlier quoted context omitted.

> It may actually be the final breakthrough we need for AGI. I disagree. As I understand them, LLMs right now don’t understand concepts. They actually don’t understand, period. They’re basically Markov chains on steroids. There is no intelligence in this, and in my opinion actual intelligence is a prerequisite for AGI.

They are capable of extracting arbitrary semantic information and generalize across it. If this is not an understanding, I don't know what is.

To me, understanding the world requires experiencing reality. LLMs dont experience anything. They’re just a program. You can argue that living things are also just following a program but the difference is that they (and I include humans in this) experience reality.

Re: Claude’s memory architecture is the opposite of ChatGPT’s

#39
What are the barriers to external memory stores (assuming similar implementations), used via tool calling or MCP? Are the providers RL’ing their way into making their memory implementations better, cementing their usage, similar to what I understand is done wrt tool calling? (“training in” specific tool impls)

I am coming from a data privacy perspective; while I know the LLM is getting it anyway, during inference, I’d prefer to not just spell it out for them. “Interests: MacOS, bondage, discipline, Baseball”

Re: Claude’s memory architecture is the opposite of ChatGPT’s

#40
post #9

The link to the breakdown of ChatGPT's memory implementation is broken, the correct link is: https://www.shloked.com/writing/chatgpt-memory-bitter-lesson This is really cool, I was wondering how memory had been implemented in ChatGPT. Very interesting to see the completely different approaches. It seems to me like Claude's is better suited for solving technical tasks while ChatGPT's is more suited to improving casual…

> It may actually be the final breakthrough we need for AGI. I disagree. As I understand them, LLMs right now don’t understand concepts. They actually don’t understand, period. They’re basically Markov chains on steroids. There is no intelligence in this, and in my opinion actual intelligence is a prerequisite for AGI.

>They’re basically Markov chains on steroids. There is no intelligence in this, and in my opinion actual intelligence is a prerequisite for AGI.

This argument is circular.

A better argument should address (given the LLM successes in many types of reasoning, passing the turing test, and thus at producing results that previously required intelligence) why human intelligence might not also just be "Markov chains on even better steroids".

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